Abstract
Background
At present, the etiology and mechanism of ovarian dysfunction are still unclear.Recent studies have indicated a potential correlation between immunity and ovarian dysfunction. However, the causal relationship between the immune cells and ovarian dysfunction still remains uncertain. For this aiticle,we aimed to figure out whether changes of immune cell composition contribute to ovarian dysfunction in this article.
Methods
Comprehensive two-sample Mendelian randomization analysis was performed to determine the causal role between immune cell compostitions and ovarian dysfunction in this study. The immune cell data are derived from the latest GWAS blood cell shape summary statistical data from the GWAS Catalog, and ovarian dysfunction data were obtained from the IEU Open GWAS. A total of 942 cases and 18,228 controls were included. A variety of analytical methods, including inverse variance weighting, weighted median, and MR-Egggera etc, were utilized to explore the link between immune cells and ovarian dysfunction. The Cochran's Q statistics were used to evaluate the heterogeneity of instrumental variables. The MR-Egger and MR pleiotropic residuals and outlier tests were utilized to detect the horizontal pleiotropy. The funnel plots and scatter plots visually assess heterogeneity and robustness.
Results
Our findings suggest that the presence of 36 immune phenotypes had a significant causal effect on ovarian dysfunction. Among them, 18 immunophenotypes were positively associated with ovarian dysfunction, including 7 in the B cell panel, 9 in the T cell panel, 1 in the monocyte cell panel and 1 in the NK cell panel; 28 immunophenotypes were negatively associated with ovarian dysfunction, including 11 in the B cell panel, 14 in the T cell panel, and in the monocyte cell panel.
Conclusion
Our study has demonstrated the close connection between immune cells and ovarian dysfunction by genetic background analysis. Further research is necessary to evaluate the potential of these immunophenotypes as early predictors of ovarian dysfunction, as well as possibility of new preventive strategies and new therapeutic targets.